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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 Hits 1 – 20 of 36 1 A Neural Pairwise Ranking Model for Readability Assessment ... Lee, Justin; Vajjala, Sowmya. - : arXiv, 2022 BASE Show details 2 Vikidia En/Fr bilingual dataset for Automatic Readability Assessment ... Lee, Justin; Vajjala, Sowmya. - : Zenodo, 2022 BASE Show details 3 Vikidia En/Fr bilingual dataset for Automatic Readability Assessment ... Lee, Justin; Vajjala, Sowmya. - : Zenodo, 2022 BASE Show details 4 Universal Dependencies 2.9 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021 BASE Show details 5 Universal Dependencies 2.8.1 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021 BASE Show details 6 Universal Dependencies 2.8 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021 BASE Show details 7 Teaching NLP outside Linguistics and Computer Science classrooms: Some challenges and some opportunities ... Vajjala, Sowmya. - : arXiv, 2021 BASE Show details 8 Are pre-trained text representations useful for multilingual and multi-dimensional language proficiency modeling? ... Rama, Taraka; Vajjala, Sowmya. - : arXiv, 2021 BASE Show details 9 Universal Dependencies 2.7 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2020 BASE Show details 10 Universal Dependencies 2.6 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2020 BASE Show details 11 Are You Being Rhetorical? An Open Corpus of Machine Annotated Rhetorical Moves Knight, Simon; Abel, Sophie; Shibani, Antonette... In: English Publications (2020) BASE Show details 12 Linguistic Metrics for Patent Disclosure: Evidence from University versus Corporate Patents Kong, Nancy; Vajjala, Sowmya; Dulleck, Uwe. - : Munich: Center for Economic Studies and Ifo Institute (CESifo), 2020 BASE Show details 13 Universal Dependencies 2.5 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2019 BASE Show details 14 Universal Dependencies 2.4 Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2019 BASE Show details 15 Universal Dependencies 2.2 Nivre, Joakim; Abrams, Mitchell; Agić, Željko... In: https://hal.archives-ouvertes.fr/hal-01930733 ; 2018 (2018) BASE Show details 16 Universal Dependencies 2.3 Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2018 BASE Show details 17 Universal Dependencies 2.2 Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2018 BASE Show details 18 Experiments with Universal CEFR Classification ... Vajjala, Sowmya; Rama, Taraka. - : arXiv, 2018 BASE Show details 19 Machine Learning and Applied Linguistics ... Vajjala, Sowmya. - : arXiv, 2018 BASE Show details 20 Experiments with Universal CEFR Classification Vajjala, Sowmya; Rama, Taraka In: English Conference Papers, Posters and Proceedings (2018) Abstract: The Common European Framework of Reference (CEFR) guidelines describe language proficiency of learners on a scale of 6 levels. While the description of CEFR guidelines is generic across languages, the development of automated proficiency classification systems for different languages follow different approaches. In this paper, we explore universal CEFR classification using domainspecific and domain-agnostic, theory-guided as well as data-driven features. We report the results of our preliminary experiments in monolingual, cross-lingual, and multilingual classification with three languages: German, Czech, and Italian. Our results show that both monolingual and multilingual models achieve similar performance, and cross-lingual classification yields lower, but comparable results to monolingual classification. Keyword: and Multicultural Education; and Research; Bilingual; Educational Assessment; Evaluation; Language and Literacy Education; Multilingual URL: https://lib.dr.iastate.edu/engl_conf/9 https://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=1008&context=engl_conf BASE Hide details Page: 1 2

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